• Journal of Korea Multimedia Society
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• v.10 no.9
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• pp.1117-1124
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• 2007

In this paper, an algorithm that can define the threshold value automatically proposed in order to detect a brain ventricle in MRI brain images. After the wavelet transform, edge sharpness, which means the average magnitude of detail signals on the contour of the object, was computed by using the magnitude of horizontal and vertical detail signals. The contours of a brain ventricle were detected by increasing the threshold value repeatedly and computing edge sharpness. When the edge sharpness became maximal, the optimal threshold was determined, and the detection of a brain ventricle was accomplished finally. In this paper, we compared the proposed algorithm with the geodesic active contour model numerically and verified the efficiency of the proposed algorithm by applying real MRI brain images.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.10 no.3
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• pp.123-129
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• 1985

This paper describes the determination of threshold value in order to determine the presence of absence of weak signal with SNR of 0 dB in 100kHz bandwidth. As a detection method, it has been used a recent LOC structure fitting for detecting weak signal in stead of a conventional method like Neyman-Peason crtical criterion. The signal for detection is the OOK modulation signal used in data and morse code transmission. The non-Gaussian noise similar to Laplacian type has been chosen in transmission path. As a result of experiment, comparing probability of detection by one critical point with that by two critical points with fixing as arbitrary false alarm probability, we have found that method has been shown to be better than the conventional method.

• The Journal of Korean Association of Computer Education
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• v.8 no.6
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• pp.103-111
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• 2005

This paper presents a novel automated threshold-decision algorithm that uses the mean and standard-deviation values obtained from the difference values of consecutive frames. At first, the calculation of difference values is obtained by the weighted ${\chi}^2$-test algorithm which was modified by joining color histogram to ${\chi}^2$-test algorithm. The weighted ${\chi}^2$-test algorithm can subdivide the difference values by imposing weights according to NTSC standard. In the first step, the proposed automatic threshold-decision algorithm calculates the mean and standard-deviation value from the total difference values, and then subtracts the mean value from the each difference values. In the next step, the same process is performed on the remained difference values, and lastly, the threshold is detected from the mean when the standard deviation has a maximum value. The proposed method is tested on various video sources and, in the experimental results, it is shown that the proposed method efficiently estimates the thresholds and reliably detects scene changes.

• Journal of Broadcast Engineering
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• v.19 no.6
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• pp.967-970
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• 2014

An efficient peak detection algorithm in magnitude spectrum is proposed to distinguish the M-frequency shift keying(FSK) signals from other digitally modulated signal. In addition, recognition of the modulation order estimation of FSK signals is also studied based on the fact that the magnitude spectrum of FSK signals reveals the number of peaks equal to the modulation order. When no a priori information about the signals, we utilize the histogram of the magnitude spectrum to determine the threshold which is important factor in peak detection algorithm. The simulation results show high probability of classification under 500 symbols and signal-to-noise ratio(SNR) higher than 4dB.

• Journal of Korea Multimedia Society
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• v.8 no.4
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• pp.482-491
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• 2005

In this paper, we proposed the microcalcification detection algorithm which is based on wavelet transform and automatic thresholding method in the X-ray mammographic images. Digital X-ray imaging system is essential equipment in the field diagnosis and is widely used in the various fields such as chest, fracture of a bone, and dental correction. Especially, digital X-ray mammographic imaging is known as the most important method to diagnose the breast cancer, many researches to develop the imaging system are processing in country. In this paper, we proposed a microcalcifications detection algorithm necessary in the early phase of breast cancer diagnosis and showed that a algorithm could effectively detect microcalfication and could aid diagnosis-radiologist.

• Journal of Satellite, Information and Communications
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• v.8 no.1
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• pp.66-70
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• 2013

In this paper, Threshold setting method is proposed to improve detection probability for cooperative sensing. Even if cooperative users have all same false alarm rate, each user has different threshold due to pass ad-hoc channel. threshold level is related to detection probability. So, we select the highest threshold among cooperative users and then share threshold information for getting the high detection probability.

• The Transactions of the Korea Information Processing Society
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• v.3 no.6
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• pp.1607-1615
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• 1996

A new simply computable operator named DBAH(difference between arithmetic mean and mean)and fuzzy reasoning technique of local thresholds for extracting sketch features are proposed in this paper.The DBAH operator provides some advantages, for example dependence on local intensities and small reponses with small rates of intensity change in very dark regions. Also, the proposed fuzzy reasoning technique has a good performance extracting sketch features without human intervention.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.33 no.10A
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• pp.949-955
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• 2008

In this paper, we propose the improved energy detector using adaptive thresholds in cognitive radio system, in order to compensate the weak points of the existing energy detector in the distorted communication environment. In addition, by investigating the several parameters we analyze its performance. The numerical results show the proposed method may get the performance gain, when the mobile speed is slow (3 km/h) as well as the false alarm probability is low ($P_f=10^{-1}$).

• Proceedings of the Korea Information Processing Society Conference
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• 2000.10b
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• pp.1349-1352
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• 2000

대용량의 동영상 데이터 이용에 있어 효과적인 동영상 검색을 위해서는 동영상 데이터의 색인과정이 필요하다. 본 논문은 AVI 영상에서의 내용기반 색인에 기초가 될 동영상의 장면 변환점 검출에 관한 효과적인 방법을 제안하고자 한다. 제안된 방법은 프레임을 블록화 시켜 대각선 방향으로 블록간의 ALH(Average of Luminance Histogram)를 비교하여 일정한 임계치에 도달하지 못할 경우 이 프레임을 장면 변환점으로 검출하게 된다. 점진적 장면의 변화에 대비하기 위해 장면 변환점이 추출될 때까지 임계치 값을 낮춰줌으로서 정확한 장면 전환 지점을 검출하고자 한다.

• Journal of Korea Multimedia Society
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• v.7 no.5
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• pp.744-754
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• 2004

In this paper, a polarity based blind watermarking method considering wavelet coefficients modification is proposed. In this proposed method, we use an asymmetric thresholds watermarking(ATW) in which detection threshold is higher than inserting threshold in order to enhance watermark detection ratio in attacked images. Also, in order to reduce errors in the detected value of watermarks according to small changes in the coefficient values when detecting watermarks, it set the range for movement variation of the coefficients and lowered the sensitivity of variation by ignoring the variations that fall into this range. For this purpose, the polarity preservation threshold $\beta$ was set and a watermark was detected based on the polarity only for the difference that was larger than $\beta$. The experimental results show that the proposed method has good quality and is robust to various attacks such as the JPEG lossy compression, noise addition, cropping, blurring, etc.